bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Polypyrimidine Tract Binding Proteins are essential for B cell development
Authors:
Elisa Monzón-Casanova1,2*, Louise S. Matheson1, Kristina Tabbada3, Kathi Zarnack4,
Christopher W. J. Smith2 and Martin Turner1*
Affiliations:
1Laboratory of Lymphocyte Signalling and Development, The Babraham Institute,
Cambridge, UK;
2Department of Biochemistry, University of Cambridge, Cambridge, UK;
3Next Generation Sequencing Facility, The Babraham Institute, Cambridge, UK;
4Buchmann Institute for Molecular Life Sciences, Goethe University Frankfurt, Frankfurt
am Main, Germany
*Corresponding authors:
Elisa Monzón-Casanova ([email protected]) and Martin Turner
1 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Abstract
During B cell development, recombination of immunoglobulin loci is tightly coordinated
with the cell cycle to avoid unwanted rearrangements of other genomic locations. Several
factors have been identified that suppress proliferation in late-pre-B cells to allow light
chain recombination. By comparison, our knowledge of factors limiting proliferation
during heavy chain recombination at the pro-B cell stage is very limited. Here we identify
an essential role for the RNA-binding protein Polypyrimidine Tract Binding Protein 1
(PTBP1) in B cell development. Absence of PTBP1 and the paralog PTBP2 results in a
complete block in development at the pro-B cell stage. PTBP1 promotes the fidelity of the
transcriptome in pro-B cells. In particular, PTBP1 controls a cell cycle mRNA regulon,
suppresses entry into S-phase and promotes progression into mitosis. Our results
highlight the importance of S-phase entry suppression and post-transcriptional gene
expression control by PTBP1 in pro-B cells for proper B cell development.
2 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Introduction
During development B cells first rearrange VDJ gene segments of their immunoglobulin
heavy chain (Igh) locus and subsequently VJ gene segments from their immunoglobulin
light (Igl) loci to generate antibody diversity (Supplementary Fig. 1a). A burst in
proliferation at the early-pre-B cell stage occurs once developing B cells have successfully
recombined their Igh locus (Herzog et al., 2009). V(D)J recombination occurs during
G0/G1 phase of the cell cycle (Schlissel et al., 1993) and RAG proteins are degraded upon
entry into S-phase to suppress V(D)J recombination (Li et al., 1996). Therefore,
alternation between proliferative and non-proliferative stages during B cell development
is precisely controlled (Herzog et al., 2009; Clark et al., 2014). Several factors have been
identified that suppress proliferation in late-pre-B cells and allow Igl recombination
including interferon regulatory factors-4 and -8 (Irf4, Irf8) (Lu et al., 2003), Ras (Mandal
et al., 2009), Ikaros and Aiolos (Ma et al., 2010), BCL-6 (Nahar et al., 2011), dual specificity
tyrosine-regulated kinase 1A (DYRK1A) (Thompson et al., 2015), B cell translocation
gene 2 (BTG2) and protein arginine methyl transferase 1 (PRMT1) (Dolezal et al., 2017).
By comparison, we are only beginning to understand mechanisms that control
proliferation in pro-B cells. At this stage, cell cycle progression driven by IL-7 is
segregated from Igh recombination (Johnson et al., 2012) and the RNA-binding proteins
(RBPs) ZFP36L1 and ZFP36L2 suppress proliferation allowing Igh recombination and B
cell development (Galloway et al., 2016).
A network of transcription factors controls development and identity in B cells
(Busslinger, 2004). After transcription, RBPs control messenger RNA (mRNA) expression
and coordinate functionally related genes in mRNA regulons (Keene, 2007). Control of
3 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
cell cycle mRNA regulons by RBPs is fundamental for early lymphocyte development
(Galloway and Turner, 2017). Polypyrimidine Tract Binding Proteins (PTBP) are RBPs
that control alternative splicing, alternative polyadenylation, mRNA stability and
translation (Hu et al., 2018; Knoch et al., 2004; 2014). PTBP1 can either increase or
decrease mRNA stability by binding to the 3’UTR of transcripts or by modulating
alternative splicing of exons that will form transcript isoforms degraded by nonsense-
mediated mRNA decay (NMD) (Hu et al., 2018). PTBP1 is expressed ubiquitously. PTBP2
and PTBP3 (formerly ROD1) are highly conserved paralogs of PTBP1 expressed in
neurons and hematopoietic cells, respectively. PTBP1 suppresses expression of PTBP2
directly by inducing Ptbp2 exon 10 skipping and mRNA degradation by NMD (Boutz et
al., 2007). In germinal centre B cells, PTBP1 promotes proliferation, the c-MYC gene
expression program induced upon positive selection and antibody affinity maturation
(Monzon-Casanova et al., 2018). PTBP1 and PTBP2 have specific and redundant functions
(Spellman et al., 2007; Vuong et al., 2016; Ling et al., 2016). Therefore, expression of
PTBP2 in PTBP1-deficient cells compensates for many functions of PTBP1 (Spellman et
al., 2007; Vuong et al., 2016; Ling et al., 2016; Monzon-Casanova et al., 2018).
To study the roles of PTBP1 controlling post-transcriptional gene expression in B cells,
we and others deleted Ptbp1 in pro-B cells and found normal B cell development
accompanied by PTBP2 expression (Monzon-Casanova et al., 2018; Sasanuma et al.,
2019). Here we addressed the functions of PTBP in B cell development by deleting both
Ptbp1 and Ptbp2 in pro-B cells. We show that PTBP1, and in its absence PTBP2, are
essential to promote B cell lymphopoiesis. In pro-B cells PTBP1 suppresses entry into S-
phase and promotes entry into mitosis after G2-phase. At the molecular level, PTBP1 is
4 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
necessary to maintain transcriptome fidelity in pro-B cells and is an essential component
of a previously unrecognised cell cycle mRNA regulon.
5 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Results
Redundancy between PTBP1 and PTBP2 for B cell development
As both PTBP1 and PTBP3 are expressed in mature B cells (Monzon-Casanova et al.,
2018) we determined their expression during defined stages of B cell development in
mouse bone marrow (Supplementary Fig. 1a-d). Fluorescence intensity of intracellular
PTBP1 staining by flow cytometry was greater in pro- and early-pre-B cells compared to
late-pre-B and immature-B cells. However, the isotype control staining for PTBP1 showed
the same differences in fluorescence intensity (Supplementary Fig. 1c, d). Therefore,
PTBP1 protein expression was similar between the different bone marrow B cell
populations. PTBP3 protein detected with a specific monoclonal antibody (Monzon-
Casanova et al., 2018) was also relatively constant throughout B cell development
(Supplementary Fig. 1c, d). PTBP2 protein was not detected in any of the B cell
developmental stages analysed (Supplementary Fig. 1c, d). Thus, PTBP1 and PTBP3, but
not PTBP2, are co-expressed throughout B cell development.
Conditional deletion of a Ptbp1-floxed allele (Suckale et al., 2011) in pro-B cells with the
Cd79acre allele (Cd79acre/+Ptbp1fl/fl mice, denoted here as Ptbp1 single conditional knock-
out, P1sKO) did not affect B cell development and resulted in the expression of PTBP2
(Monzon-Casanova et al., 2018). Therefore, we generated a double conditional knock-out
(dKO) mouse model where both Ptbp1 and Ptbp2 were deleted in pro-B cells using floxed
alleles and Cd79acre (Cd79acre/+Ptbp1fl/flPtbp2fl/fl mice, denoted here as P1P2dKO).
Deletion of both Ptbp1 and Ptbp2 in pro-B cells resulted in the absence of mature B cells
in the spleen and lymph nodes (Fig. 1a, b and Supplementary Fig. 1e).
6 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
PTBPs are required for progression beyond the pro-B cell stage
The absence of mature B cells in P1P2dKO mice resulted from a block in B cell
development at the pro-B cell stage (Fig. 1c, d and Supplementary Fig. 1a). We
confirmed the lack of PTBP proteins in pro-B cells from the conditional KO mice
(Supplementary Fig. 2a, b). PTBP1 protein was absent in P1sKO and P1P2dKO pro-B
cells and Ptbp1 deletion led to the expression of PTBP2 in P1sKO pro-B cells
(Supplementary Fig. 2b). P1P2dKO pro-B cells failed to increase PTBP2 in response to
Ptbp1 deletion, validating our dKO. P1P2dKO pro-B cells expressed increased amounts of
PTBP3 compared to pro-B cells from littermate control mice (Cd79a+/+Ptbp1fl/flPtbp2fl/fl,
denoted here as “control” unless stated otherwise) (Supplementary Fig. 2b). Yet, PTBP3
was insufficient to compensate for the lack of PTBP1 and PTBP2 in pro-B cells (Fig. 1c,
d), demonstrating an irreplaceable role for PTBP1 in B cell development in the absence
of PTBP2.
Characterisation of B cell development distinguishing between pro-, early- and late-pre-
B cells revealed an increase in the numbers of early-pre-B cells in P1sKO compared to
control mice and to Cd79acre “Cre-only” mice (mb1, Cd79aCre/+Ptbp1+/+Ptbp2+/+) (Fig. 1d).
In contrast, the numbers of late-pre- and immature-B cells were similar between P1sKO
and control mice (Fig. 1d). These data confirmed that deletion of Ptbp1 alone results in
largely unaffected B cell development.
In P1P2dKO mice there were similar numbers of FrB pro-B cells (B220+, CD19+, IgM-,
CD43high, CD24+, CD249low) and FrC pro-B cells (B220+, CD19+, IgM-, CD43high, CD24+,
CD249high) compared to littermate control and to Cd79acre “Cre-only” mice but we did not
find FrC’ early-pre-B cells, characterised by high expression of CD24 and CD249 (detected
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by BP-1) (Fig. 1d). P1P2dKO FrB and FrC pro-B cells have higher CD24 staining than
control FrB and FrC pro-B cells (Fig. 1c). Therefore, we set different gates in the P1P2dKO
mice to include all these cells. FrB and FrC pro-B cells from P1P2dKO mice showed
increased c-KIT (CD117) staining compared to P1sKO and control pro-B cells and lacked
CD2, corroborating a block at an early developmental stage (Supplementary Fig. 2c, d).
With a cell surface and intracellular staining (Supplementary Fig. 2a) to identify early
and late pre-B cells as cells with successfully rearranged intracellular Igµ chain we
confirmed the block in B cell development in P1P2dKO mice at the pro-B cell stage
(Supplementary Fig. 2a, e). With this gating strategy the numbers of pro-B cells in
P1P2dKO mice were reduced compared to P1sKO and control mice. Few early-pre-B cells
(B220+, CD19+, IgM-, CD93+, CD43high, Igµ+) were present in P1P2dKO mice indicating
some successful recombination of the Igh locus in P1P2dKO pro-B cells (Supplementary
Fig. 2a). However, the numbers of early-pre-B cells were decreased by ~13-fold in
P1P2dKO compared to control mice (Supplementary Fig. 2e). Compared to the numbers
of pro-B cells in Rag2-/- deficient mice, the numbers of P1P2dKO pro-B cells identified by
the two different staining strategies were decreased by ~4.6-fold (FrB), 19-fold (FrC)
(Fig. 1d) and 47-fold (pro-B, Supplementary Fig. 2e). Thus, when Igh recombination is
defective in Rag2-/- mice developing B cells accumulate at the pro-B cell stage, whereas in
P1P2dKO mice pro-B cells do not accumulate.
PTBP1 suppresses entry into S-phase in pro-B cells
Dynamic control of proliferation is essential for successful B cell development (Clark et
al., 2014; Galloway and Turner, 2017). Therefore, we assessed the proliferative status of
pro-B cells in the P1P2dKO mice. To identify cells in early-, late- or post-S-phase we
sequentially labelled cells in vivo with EdU and BrdU (Fig. 2a). With this approach, cells
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that incorporate only EdU were in S-phase at the beginning, but not at the end of the
labelling period and are in post S-phase; cells that incorporate both EdU and BrdU are in
late S-phase; and cells labelled only with BrdU at the end of the labelling period are in
early S-phase. In control mice, we detected few pre-pro-B cells in S-phase (3.8% in early-
and late-S together), compared to 13% of pro-B cells and high frequencies (53%) of early-
pre-B cells in S-phase (Supplementary Fig. 3a-d). In P1P2dKO pro-B cells the
proportions of early-S-phase cells were increased 4.7-fold compared to control and 3.2-
fold compared to P1sKO pro-B cells (Fig. 2b, c). The numbers of early-S-phase P1P2dKO
pro-B cells were similar to those of P1sKO and control pro-B cells (Fig. 2d). However, the
numbers of the whole pro-B cell population identified with the combination of cell
surface and intracellular markers (IgD-IgM-B220+CD19+CD43highIgµ+) used with the EdU
and BrdU labelling approach (Supplementary Fig. 3a) were reduced 4.4-fold in
P1P2dKO compared to control mice (Fig. 2d). Therefore, it is unlikely that the increased
proportions in early S-phase amongst P1P2dKO pro-B cells result from reduced numbers
of pro-B cells in G0/G1-phase. Thus, in the absence of PTBP1 and PTBP2 pro-B cells enter
S-phase more readily. The proportions of P1P2dKO pro-B cells in late S-phase and post
S-phase were also increased compared to P1sKO pro-B cells and control pro-B cells (Fig.
2c). The magnitude of the increase in the proportions of cells in post S-phase was smaller
than the increase in either early- or late-S-phase. This indicated that P1P2dKO pro-B cells
enter S-phase more readily than control pro-B cells but they fail to progress through S-
phase at the same pace as PTBP1-sufficient pro-B cells.
PTBP1 is required for the transition from G2 to M phase in pro-B cells
We also analysed cells in G2/M-phases by detecting DNA synthesis in combination with
DNA content (Fig. 2e, Supplementary Fig. 3e, f). The proportion of P1P2dKO pro-B cells
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in G2/M-phase was increased ~40-fold compared to P1sKO and control pro-B cells (Fig.
2e, f) and the numbers of G2/M-phase pro-B cells in P1P2dKO mice were increased ~8-
fold compared to control and P1sKO mice (Fig. 2e, f). These findings were confirmed
when identifying FrB pro-B cells using cell surface markers (CD19+, CD24+, CD249-, CD2-
, CD25-, IgM-, IgD-), EdU labelling and DNA staining (Supplementary Fig. 3g, h). To
preserve phosphorylated histone 3 (pH3), which marks cells in mitosis, during the
staining process and quantitating DNA content with sufficient resolution, we identified
FrB pro-B cells again with cell surface markers (CD19+, CD24+, CD249- , CD2-, CD25-, IgM-
, IgD-) (Supplementary Fig. 3g, i). Some P1P2dKO pro-B cells had high pH3 levels
amongst cells with 4N-DNA content (Supplementary Fig. 3i). However, the proportions
of pH3-positive cells amongst P1P2dKO pro-B cells with 4N-DNA content were reduced
compared to the proportions found amongst P1sKO and control pro-B cells
(Supplementary Fig. 3i, j). Therefore, the majority of P1P2dKO pro-B cells with 4N-DNA
content are in G2-phase and have not entered mitosis. PTBP1 is thus required in pro-B
cells to progress from G2 to M-phase of the cell cycle.
A block in G2-phase is a hallmark response to DNA damage. Therefore, we assessed
markers of DNA damage at different stages of the cell cycle by flow cytometry
(Supplementary Fig. 4). G0/G1 P1P2dKO pro-B cells are bigger compared to P1sKO and
control G0/G1 pro-B cells (FSC-A measurements, Supplementary Fig. 4a). This is
consistent with a predisposition to enter S-phase, as size increase and S-phase entry are
positively correlated (Ginzberg et al., 2015). This increase in size resulted in higher
intracellular background staining with isotype-control antibodies in G0/G1 P1P2dKO
pro-B cells compared to G0/G1 P1sKO and control pro-B cells (Supplementary Fig. 4b,
c). pH2AX staining in P1P2dKO pro-B cells was not increased compared to P1sKO and
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control pro-B cells above the increase seen in background staining controls
(Supplementary Fig. 4b, c). Staining of bone marrow cells treated with etoposide to
induce DNA damage showed that P1P2dKO pro-B cells increased pH2AX levels to the
same extent as P1sKO and control pro-B cells (Supplementary Fig. 4d, e). We found an
increase (2.1-fold) in p53 staining in P1P2dKO G0/G1 pro-B cells compared to control
G0/G1 pro-B cells above the increase (1.6-fold) seen in background staining controls
(Supplementary Fig. 4f, g). Upon etoposide treatment, the fold increase in p53 in
P1P2dKO G0/G1 pro-B cells compared to control pro-B cells (2.5-fold) was higher than
in pro-B cells without etoposide treatment (2.1-fold) (Supplementary Fig. 4g). Thus,
p53 levels provide some evidence of DNA damage in pro-B cells lacking PTBP1 and
PTBP2 but these DNA damage levels are insufficient to be detected by pH2AX-staining.
Therefore, DNA damage in P1P2dKO pro-B cells could contribute to the block in G2-
phase.
PTBP1 is necessary to maintain transcriptome fidelity in pro-B cells
To identify the consequences of PTBP deficiency on the transcriptome of pro-B cells we
carried out mRNAseq with polyadenylated transcripts from P1P2dKO, P1sKO and control
cKIT+ pro-B (FrB) cells (Supplementary Fig. 5). To identify candidate transcripts
directly bound and regulated by PTBP1 we made use of a PTBP1 individual-nucleotide
resolution Cross-Linking and ImmunoPrecipitation (iCLIP) (König et al., 2010) dataset
which reveals PTBP1-binding sites in the whole transcriptome and thereby allows
distinction between direct and indirect targets. The PTBP1 iCLIP data was from mitogen-
activated mouse primary B cells (Monzon-Casanova et al., 2018) because it was not
feasible to purify sufficient numbers of pro-B cells for iCLIP. There is a positive
correlation between the transcriptomes from mitogen-activated primary B cells and pro-
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B cells (Supplementary Fig. 6a), suggesting that the available PTBP1 iCLIP data set
(Supplementary Tables 1, 2) allows to infer direct interactions of PTBP1 in pro-B cells.
We analysed changes in mRNA abundance by comparing pro-B cell transcriptomes from
the different genotypes in pairwise comparisons (Fig. 3a). There were more genes
showing differential mRNA abundance when comparing P1P2dKO to control pro-B cells
(1226 genes) and P1P2dKO to P1sKO pro-B cells (1202 genes) than when comparing
P1sKO to control pro-B cells (214 genes) (using a log2-transformed fold change >|0.5| and
FDR <0.05, Supplementary Table 3). We found that only ~25% of the genes with either
increased or decreased mRNA abundance due to absence of both PTBP1 and PTBP2 were
directly bound by PTBP1 at the 3’UTR and are therefore likely to be direct targets
(Supplementary Fig. 6b and Supplementary Table 3). The remaining changes
observed in mRNA abundance upon Ptbp1 and Ptbp2 deletion can be expected to be
independent from a direct role of PTBP1 via 3’UTR binding. Ptbp2 mRNA abundance was
increased ~18-fold in P1sKO compared to control pro-B cells (Fig. 3a, Supplementary
Table 3). Similarly, P1P2dKO pro-B cells showed an upregulation (~6.8-fold) of Ptbp2
mRNA compared to control pro-B cells (Fig. 3a, middle plot). However, Ptbp2 transcripts
in P1P2dKO pro-B cells lack Ptbp2 exon 4 due to the conditional knock-out
(Supplementary Fig. 6c), and hence do not result in PTBP2 protein expression
(Supplementary Fig. 2b).
We assessed alternative splicing (AS) differences in pro-B cells with different genotypes
by computing differences in exon inclusion levels in pairwise comparisons with rMATS
(Shen et al., 2014) (Fig. 3b, Supplementary Table 4). rMATS considers five different
types of alternatively spliced events: skipped exons, mutually exclusive exons, alternative
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5’ and 3’ splice sites (SS) and retained introns (Supplementary Fig. 6d). The inclusion
level of a particular AS event is the proportion (scaled to 1) of transcripts containing the
alternatively spliced mRNA segment. We chose a threshold of an absolute inclusion level
difference >0.1 to identify substantial changes in AS. Similar to our observations in mRNA
abundance, the absence of both PTBP1 and PTBP2 in pro-B cells resulted in more
differentially alternatively spliced events (P1P2dKO – Ctrl, 1599 events in 1058 genes)
than the absence of PTBP1 (P1sKO – Ctrl, 865 events in 659 genes) (Fig. 3b). Depending
on the type of AS event analysed, from 30 to 50% of the events with changes in AS, when
comparing P1P2dKO to control pro-B cells, were bound in their vicinity by PTBP1
(Supplementary Fig. 6e, Supplementary Table 4). This implicates PTBP1 in controlling
these AS events directly. There is a small overlap of genes with changes in mRNA
abundance and also AS in the different pairwise comparisons (Fig. 3c), indicating that the
inclusion of certain exons may generate NMD targets. Such AS events promoting NMD are
most likely underestimated, since the RNA containing these events will be degraded and
it might be difficult to detect by mRNAseq.
As B cell development is largely unaffected in P1sKO mice we focused on differences in
mRNA abundance and AS unique to P1P2dKO pro-B cells compared to both P1sKO and
control pro-B cells to identify changes causing the developmental block in P1P2dKO mice.
We identified 1021 and 611 genes with decreased and increased mRNA abundance,
respectively, in P1P2dKO compared to control and P1sKO pro-B cells (Fig. 3d). Amongst
AS changes, we found 971 genes with increased or decreased inclusion levels of at least
one event in P1P2dKO pro-B cells compared to control and P1sKO (Fig. 3e). When
addressing abundance changes, P1P2dKO pro-B cells cluster separately from P1sKO and
control pro-B cells (Fig. 3d). In contrast, when analysing AS, P1P2dKO and P1sKO pro-B
13 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
cells cluster together and separately from control pro-B cells (Fig. 3e). Therefore, PTBP2
is more able to compensate for the absence of PTBP1 at the mRNA abundance than at the
AS level. We observed only few genes with different mRNA abundance (cluster d) or
changes in AS (clusters i and iii) that were predominantly regulated in P1sKO pro-B cells
compared to P1P2dKO and control pro-B cells (Fig. 3d, e). In contrast, large numbers of
genes had different mRNA abundance (clusters a, b and c) and AS (clusters ii and iv) in
P1P2dKO pro-B cells compared to P1sKO and control pro-B cells (Fig. 3d, e). Therefore,
in pro-B cells, PTBP2 has only few specific targets and mostly compensates for the
absence of PTBP1. We conclude that in pro-B cells PTBP1 ensures appropriate expression
at the level of AS and mRNA abundance level of more than 2000 genes and therefore
promotes the fidelity of their transcriptome.
PTBP1 controls CDK activity in pro-B cells
To assess functions of the genes with altered expression in P1P2dKO pro-B cells we
carried out gene ontology (GO) enrichment analysis on genes with increased or reduced
abundance or with AS changes. We found numerous enriched GO terms important for the
biology of B cells and their progenitors (Fig. 4a, Supplementary Table 5) such as
“antigen processing and presentation of peptide antigen via MHC class II” amongst genes
with increased abundance and “positive regulation of DNA-binding transcription factor
activity” amongst genes with decreased abundance. We found enrichment of terms
related to migration such as “neuronal crest migration” and “neutrophil migration”. At
the AS level, enrichment of the term “cytoskeletal protein binding” suggests PTBP1 as a
cytoskeleton regulator. “Regulation of neuron differentiation” was enriched amongst
genes with reduced abundance and with changes in AS, as we expected from the known
roles of PTBPs in neuronal development (Hu et al., 2018). Thus, PTBP1 is necessary in
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pro-B cells to promote adequate expression of many different pathways fundamental for
cell biology.
In P1P2dKO pro-B cells there were no obvious expression defects in genes important for
the progression from pro- to pre-B cells (Supplementary Fig. 6f, Supplementary
Tables 3, 4). Therefore, we focused on understanding the molecular mechanisms driving
uncontrolled entry into S-phase and increased frequencies of pro-B cells in G2-phase. We
only found one GO term amongst those enriched to be directly associated with
proliferation: “cyclin-dependent protein serine/threonine kinase inhibitor activity”. This
was unexpected given the documented changes in the transcriptome across different
phases of the cell cycle (Giotti et al., 2018) and that FrB pro-B cells from which we carried
out mRNAseq in P1P2dKO mice have a ~10% increase of cells in S-phase and ~12%
increase of cells in G2/M-phase compared to control and P1sKO FrB pro-B cells
(Supplementary Fig. 3g, h). Moreover, we did not find a global increase of S- and G2/M-
associated transcripts (Giotti et al., 2018) in the P1P2dKO pro-B transcriptome (Fig. 4b).
Instead, we found 8 genes with a reduction of mRNA abundance greater than 2-fold (<-1
Log2-fold change) in P1P2dKO compared to control pro-B cells (Supplementary Table
6). This indicates that the majority of the changes observed in the transcriptome of
P1P2dKO compared to control and P1sKO pro-B cells are not the result of comparing
populations with different proliferative status, but are reflective of an altered pro-B cell
transcriptome.
Amongst genes associated with “cyclin-dependent protein serine/threonine kinase
inhibitor activity”, we found reduced mRNA abundance in Cdkn1b, Cdkn1c, Cdkn2c and
Cdkn2d (encoding p27, p57, p18 and p19, respectively) due to PTBP1 and PTBP2 absence
15 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
(Fig. 5a). None of these CDK inhibitors has an obvious change in AS or a binding site for
PTBP1 in the 3’UTR (Supplementary Tables 2, 4). Therefore, the changes in mRNA
expression of CDK inhibitors are likely to be indirectly regulated by PTBP1. We stained
p27 protein across different phases of the cell cycle and found it to be reduced ~1.7-fold
in G0/G1 P1P2dKO pro-B cells compared to G0/G1 P1sKO and control pro-B cells (Fig.
5b, c), consistent with the decreased mRNA abundance observed in mRNA-Seq (Fig. 5a).
In contrast, p27 staining was increased ~7-fold in G2 P1P2dKO pro-B cells compared to
P1sKO and control G2 pro-B cells (Fig. 5b, c). These differences in p27 staining seen
between G0/G1 and G2 phases are consistent with an indirect role of PTBP1 in
controlling p27 expression. In addition to p27 staining, we assessed CDK activity by
measuring the extent of RB phosphorylation, which is started in G1 by CDKs and
promotes the entry into S-phase (Otto and Sicinski, 2017). Almost all P1P2dKO G0/G1
pro-B cells had phosphorylated RB whereas only ~30% of P1sKO and control G0/G1 pro-
B cells had phosphorylated RB (Fig. 5d, e), showing that P1P2dKO pro-B cells in G0/G1-
phase have abnormally high CDK activity. In contrast, P1P2dKO pro-B cells in G2-phase
had much lower proportions of cells with highly phosphorylated RB (~30%) compared
to G2 P1sKO and control pro-B cells (~70%) (Fig. 5d, e). This suggests an impaired CDK
activity amongst G2 P1P2dKO pro-B cells, consistent with high p27 levels. The
phosphorylation of threonine-592 on SAMHD1 is mediated by CDK1 (Cribier et al., 2013).
Proportions of phospho-T592-SAMHD1-positive cells amongst P1P2dKO G2 pro-B cells
were reduced compared to P1sKO and control G2 pro-B cells (Fig. 5d, e). These results
indicate a requirement of PTBPs to achieve the adequate CDK1 activity necessary to enter
mitosis. Thus, PTBPs are essential for controlling activity of CDKs in different phases of
the cell cycle in pro-B cells: to limit entry into S-phase and to promote progression
through mitosis.
16 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
PTBP1 controls expression of a cell cycle mRNA regulon in pro-B cells
The changes in expression of CDK inhibitors seemed an indirect consequence of Ptbp1
and Ptbp2 deletion and cell cycle gene sets were not enriched amongst genes with altered
mRNA expression in the P1P2dKO pro-B cells. Thus, instead of gene sets, it was possible
that individual genes with rate limiting properties for cell cycle progression, which could
also control the expression of CDK-inhibitors and CDK activities, were directly regulated
by PTBP1. Therefore, we considered further genes affected in the absence of PTBP1 and
PTBP2 but not in the absence of PTBP1 alone that are known to regulate the cell cycle
(Fig. 6). We identified nine candidate targets with direct PTBP1 binding and changes at
the levels of mRNA abundance and AS that constitute an mRNA regulon controlling the
cell cycle.
We found three genes (Foxo1, Btg2 and Rbl1) whose proteins inhibit S-phase entry with
reduced mRNA abundance in P1P2dKO compared to control and P1sKO pro-B cells (Fig.
6a). Additionally, two genes whose proteins promote entry into S-phase (Myc and Ccnd2)
showed increased mRNA abundance due to Ptbp1 and Ptbp2 deletion (Fig. 6a). FOXO
transcription factors promote p27 expression and inhibit CDK activity (Herzog et al.,
2009). PTBP1 bound to the 3’UTR of Foxo1 (Supplementary Fig. 7a). No obvious change
in Foxo1 AS was detected upon Ptbp1 and Ptbp2 deletion (Supplementary Table 4).
Therefore, PTBP1 expression enhances Foxo1 mRNA abundance in pro-B cells. PTBP1
bound to Myc 3’UTR (Supplementary Fig. 7a). We confirmed an increase of c-MYC
protein in G0/G1 P1P2dKO pro-B cells compared to control and P1sKO G0/G1 pro-B cells
(Supplementary Fig. 7b, c) as the fold-change increase in fluorescence intensity of the
c-MYC staining (2.2-fold) was greater than the fold-change increase in fluorescence
17 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
intensity of the control staining (1.5-fold). Therefore, in pro-B cells PTBP1 suppresses
Myc. CYCLIN-D2 pairs with CDK4/6. Ccnd2 abundance (encoding CYCLIN-D2) was
increased ~2-fold in P1P2dKO compared to control and P1sKO pro-B cells (Fig. 6a) and
PTBP1 bound to Ccnd2 3’UTR (Supplementary Fig. 7a). c-MYC induces transcription of
Ccnd2 (Bouchard et al., 2001). Therefore, PTBP1 and PTBP2 may reduce Ccnd2
abundance indirectly by suppressing c-MYC-mediated transcription and directly by
binding its mRNA. BTG2 inhibits G1 to S transition and promotes B cell development by
suppressing proliferation in late-pre-B cells (Dolezal et al., 2017). Btg2 mRNA abundance
was reduced ~2-fold due to Ptbp1 and Ptbp2 deletion (Fig. 6a). No obvious change in
Btg2 AS was detected but PTBP1 binding sites were present at the Btg2 3’UTR
(Supplementary Fig. 7a). Therefore, PTBP1 could directly promote BTG2 expression in
pro-B cells by stabilising Btg2 transcripts. p107 (encoded by Rbl1) represses E2F
transcription factors and entry into S-phase (Bertoli et al., 2013). Rbl1 mRNA abundance
was reduced ~1.5-fold in P1P2dKO compared to control and P1sKO pro-B cells (Fig. 6a).
PTBP1 and PTBP2 suppress the inclusion of a downstream alternative 5’SS (A5SS) in Rbl1
exon 8 which generates an NMD-target isoform in P1P2dKO pro-B cells (Fig. 6b). PTBP1
binds to adjacent regions of this alternatively spliced event (Fig. 6b). This A5SS event is
conserved in human, as PTBP1- and PTBP2-depleted HeLa cells (Ling et al., 2016) also
have an increased usage of the downstream A5SS compared to PTBP-sufficient cells
resulting in reduced RBL1 mRNA abundance (Fig. 6c, d). Therefore, PTBP1 promotes
Rbl1 expression. Collectively, deregulated expression of Foxo1, Myc, Ccnd2, Btg2 and Rbl1
in the absence of PTBP1 and PTBP2 could drive entry of pro-B cells into S-phase.
We also found transcripts important for the transition from G2 to M-phase altered in
P1P2dKO pro-B cells. The abundance of Cdc25b, Ect2, Kif2c and Kif22 was reduced (~3,
18 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
~5, ~2 and ~2-fold, respectively) in P1P2dKO compared to control and P1sKO pro-B cells
(Fig. 6a). CDC25B is a phosphatase promoting G2/M transition by activating CDK1
(Boutros et al., 2007). Cdc25b AS was unaffected by PTBP1 and PTBP2 absence and
PTBP1 bound to the Cdc25b 3’UTR (Supplementary Table 4 and Supplementary Fig.
7a). Thus, PTBP1 likely promotes Cdc25b expression by binding to its 3’UTR and
enhancing its stability. Additionally, there were three genes where their changes in
mRNA abundance can be explained by AS events leading to NMD. ECT2 controls spindle
formation in mitosis by exchanging GDP for GTP in small GTPases such as RhoA (Yüce et
al., 2005). In P1P2dKO pro-B cells Ect2 has an increased inclusion of an alternative exon
compared to P1sKO and control pro-B cells (Fig. 6b). Inclusion of this AS exon, using
either of two alternative 3’ splice sites, generates NMD-predicted transcripts. PTBP1
binds nearby this NMD-triggering exon where it is predicted to suppress exon inclusion
(Llorian et al., 2010) promoting high Ect2 mRNA levels in pro-B cells. KIF2c (MCAK) and
KIF22 (KID) are two kinesin motor family members that transport cargo along
microtubules during mitosis (Cross and McAinsh, 2014). Both have increased inclusion
of an exon that generates predicted NMD-targets in P1P2dKO compared to P1sKO and
control pro-B cells and some evidence for PTBP1 binding in adjacent regions (Fig. 6b).
This data shows that PTBP1 promotes expression of genes important for mitosis by
controlling AS linked to NMD. The altered expression of these genes in the absence of
PTBP1 and PTBP2 is likely to contribute to the high proportions of G2 cells observed in
P1P2dKO pro-B cells. Our findings place PTBP1 as a regulator of the cell cycle in pro-B
cells. PTBP1 is essential to control appropriate expression of an mRNA regulon dictating
CDK activity, progression to S-phase and entry into mitosis. In the absence of PTBP1 and
its partially redundant paralog PTBP2, the molecular control of the cell cycle in primary
pro-B cells is altered and B cell development is halted (Fig. 6e).
19 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Discussion
Here we present an essential role for PTBP1 and PTBP2 in controlling B cell development
and the proliferative status of pro-B cells. PTBP1 and PTBP2 deficiency in pro-B cells
triggered entry into S-phase and accumulation in G2-phase, causing a complete block in
B cell development. PTBP1 suppression of entry into S-phase was unanticipated since in
other systems, including germinal centre (GC) B cells, PTBP1 promoted proliferation
(Suckale et al., 2011; Shibayama et al., 2009; La Porta et al., 2016) and progression
through late S-phase (Monzon-Casanova et al., 2018). GC B cells did not tolerate deletion
of both PTBP1 and PTBP2 (Monzon-Casanova et al., 2018) and previous studies
addressing proliferation in PTBP1-deficient cells were done in the presence of PTBP2
(Suckale et al., 2011; Shibayama et al., 2009; La Porta et al., 2016). Therefore, the role of
PTBP1 in suppressing S-phase entry could be unique to pro-B cells or could be found in
other cell types if they resist the absence of PTBP1 and PTBP2 long enough to assess cell-
cycle progression.
Suppression of proliferation in pre-B cells is necessary to allow Igl recombination (Clark
et al., 2014). Similarly, in pro-B cells entry into S-phase will inhibit VDJ Igh recombination.
We have previously shown that the RNA-binding proteins ZFP36L1 and ZFP36L2
suppress proliferation in pro-B cells, facilitate Igh recombination and consequently
promote B cell development (Galloway et al., 2016). In the absence of PTBP1 and PTBP2,
expression of Zfp36l1 was normal and Zfp36l2 was increased ~1.5-fold (Supplementary
Table 3), but still there was no suppression of S-phase entry. This suggests the presence
of distinct mRNA regulons controlled by the different RBPs important to control cell cycle
20 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
entry. Our results reveal the importance of suppressing proliferation also in pro-B cells
for successful B cell development.
PTBP1 maintains the fidelity of the transcriptome in pro-B cells since the absence of
PTBP1 and PTBP2 caused changes in mRNA expression of 2000 genes. In particular,
PTBP1 expression controls a cell cycle mRNA regulon comprising Foxo1, Myc, Ccnd2,
Btg2, Rbl1, Cdc25b, Ect2, Kif22 and Kif2c. Proteins from this mRNA regulon control each
other and have downstream effects on other cell cycle regulators. FOXO proteins
suppress D-type cyclins (Schmidt et al., 2002) and promote p27 (Herzog et al., 2009). c-
MYC suppresses Cdkn1b (encoding p27) (Yang et al., 2001) and increases Ccnd2
transcription (Bouchard et al., 2001). CYCLIN-D2 promotes nuclear export and
degradation of p27 (Susaki et al., 2007) and p27 can directly inhibit CYCLIN-D-CDK4/6
complexes (Yoon et al., 2012). We found evidence for interaction of PTBP1 with these
transcripts implicating a direct role of PTBP1. Future investigations are needed to assess
which of the PTBP1-binding sites are functional and control mRNA expression. However,
since these targets regulate each other it will be difficult to deconvolute direct from
indirect effects of PTBP1 controlling this cell cycle mRNA regulon. The net outcome from
deregulation of these transcripts in the absence of PTBP1 and PTBP2 is an enhanced CDK
activity in G0/G1 pro-B cells that drives entry into S-phase and a reduced CDK activity
amongst blocked G2 pro-B cells.
Myc mRNA and protein abundance was increased due to Ptbp1 and Ptbp2 deletion in pro-
B cells and PTBP1 was bound to the Myc 3’UTR. In GC B cells lacking PTBP1 alone, part of
the c-MYC-activated gene expression program initiated upon positive selection was
reduced while c-MYC protein expression was unaffected (Monzon-Casanova et al., 2018).
21 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
PTBP2 is redundant with PTBP1 in GC B cells (Monzon-Casanova et al., 2018), therefore
it is possible that c-MYC protein would be increased in GC B cells if both PTBP1 and PTBP2
are absent. We were unable to address this because we did not detect GC B cells lacking
both PTBP1 and PTBP2 (Monzon-Casanova et al., 2018). Alternatively, PTBP1 could have
distinct roles in controlling c-MYC and its gene expression programme in different cell
types.
Deletion of Ptbp1 and Ptbp2 in pro-B cells resulted in a block in G2-phase. Since the
number of pro-B cells did not accumulate in P1P2dKO mice, it is likely that P1P2dKO pro-
B cells die after the block at G2-phase. We found increased p53 in pro-B cells deficient for
PTBP1 and PTBP2, indicating that DNA damage in pro-B cells contributes to the G2 block,
although we did not detect a DNA damage signature amongst GO enrichment analysis.
DNA damage in P1P2dKO pro-B cells could happen due to the enhanced entry into S-
phase as this causes replication stress (Zeman and Cimprich, 2013). Moreover, p27
promotes G2 arrest in response to DNA-damage (Cuadrado et al., 2009; Payne et al.,
2008). Thus, the increased p27 levels found in P1P2dKO pro-B cells blocked at G2-phase
could be a response to DNA damage. Increased p27 will inhibit CDK activity and promote
G2 block (Yoon et al., 2012). PTBP1 promotes p27 IRES-mediated translation in human
cells (Cho et al., 2005). The sequence in the human CDKN1B (encoding p27) 5’UTR-IRES
is conserved in mouse. We did not find mouse PTBP1 bound to the Cdkn1b 5’UTR in our
iCLIP data. However, a direct role of PTBP1 in promoting p27 translation could still be
possible in pro-B cells and is consistent with a reduction in p27 in G0/G1 pro-B cells due
to PTBP1 and PTBP2 absence. Nevertheless, we found increased p27 levels in G2 pro-B
cells due to Ptbp1 and Ptbp2 deletion and this would be inconsistent with PTBP1
promoting p27 expression. Additionally, CDC25B reduction has been shown to cause a
22 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
G2 block (Peco et al., 2012; Lindqvist et al., 2005). Therefore, Cdc25b reduction in
P1P2dKO pro-B cells, in addition to the other mechanisms discussed, could also
contribute to the block in G2-phase.
Various RBPs promote transcriptome fidelity by suppressing non-conserved cryptic
exons which in normal conditions should never be included and often generate NMD
targets (Ling et al., 2016; Sibley et al., 2016). Cryptic exons suppressed by PTBP1 have
been found when both PTBP1 and PTBP2 were depleted (Ling et al., 2016). These cryptic
exons are poorly conserved between mouse and human. In pro-B cells deficient for
PTBP1 and PTBP2 we found cryptic exons promoting mRNA degradation amongst cell
cycle regulators. For most of them we did not find evidence for their conservation in
human cells where PTBP1 and PTBP2 were absent (Ling et al., 2016). However, the A5SS
in Rbl1 generating an NMD-target was conserved in human, suggesting that it is a
functional AS-NMD event with a role in post-transcriptional control. Altogether, PTBP1
expression in pro-B cells controls correct expression of thousands of genes. In particular,
PTBP1 controls a network of factors essential to avoid S-phase entry followed by a G2
block and to promote B cell development beyond the pro-B cell stage.
23 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Methods
Mice
Mice were bred and maintained in the Babraham Institute Biological Support Unit under
Specific Opportunistic Pathogen Free (SOPF) conditions. After weaning, mice were
transferred to individually ventilated cages with 1-5 mice per cage. All experiments were
carried out without blinding or randomization on 7 to 15-week-old mice. Conditional
knockout mice used were derived from crossing the following transgenic strains:
Ptbp1fl/fl(Ptbp1tm1Msol) (Suckale et al., 2011), Ptbp2fl/fl(Ptbp2tm1.1Dblk) (Li et al., 2014) and
Cd79acre(Cd79atm1(cre)Reth) (Hobeika et al., 2006). Rag2-/- knockout mice (Shinkai et al.,
1992) (Rag2tm1Fwa) were also used. All mice were on a C57BL/6 background.
In vivo EdU and BrdU administration
All procedures performed were approved by the Babraham Institute's Animal Welfare
and Experimentation Committee and the UK Home Office and followed all relevant ethical
regulations. In EdU-only and in EdU and BrdU double-labelling experiments 1 to 5 mice
of different genotypes and the same sex were kept in individually ventilated cages.
Whenever possible females were used as this allowed for a higher number of mice with
different genotypes per cage. Males and females showed the same differences in the
phenotypes observed due to PTBPs absence. In Edu-only labelling experiments mice
were injected with 1 mg EdU (5-ethynyl-2’-deoxyuridine, cat #E10415, ThermoFisher
Scientific) was injected intraperitoneally and mice were culled one hour after injection.
In EdU and BrdU (5-Bromo-2′-deoxyuridine, cat# B5002-500mg, Sigma) labelling
experiments mice were injected first with 1 mg EdU (cat #E10415, ThermoFisher
24 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Scientific) intraperitoneally, one hour later, the same mice were injected with 2 mg BrdU
and the mice were culled 1 hour and 40 minutes after the injection with EdU.
Flow cytometry
Single cell suspensions were prepared from spleens and lymph nodes by passing the
organs through cell strainers with 70 μm and 40 μm pore sizes in cold RPMI-1640 (cat#
R8758, Sigma) with 2% fetal calf serum (FCS). Single cell suspensions from bone
marrows were prepared by flushing the bone marrow from femurs and tibias and passing
the cells through a cell strainer with 40 μm pore size in cold RPMI-1640 with 2%FCS. Fc
receptors were blocked with monoclonal rat antibody 2.4G2. Cells were stained with
combinations of antibodies listed in Supplementary Table 7. Cell surface staining was
carried out for 45 minutes on ice by incubating cells with a mixture of antibodies in cold
FACS buffer (PBS +0.5%FCS). For intracellular staining cells were fixed with
Cytofix/Cytoperm™ Fixation and Permeabilization Solution (cat# 554722, BD) on ice,
washed with FACS Buffer and frozen in 10% DMSO 90% FCS at -80oC at least overnight.
After thawing, cells were washed with FACS Buffer and re-fixed with Cytofix/Cytoperm™
Fixation and Permeabilization Solution (cat# 554722, BD) for 5 minutes on ice. Cells were
washed with Perm/Wash Buffer (cat# 554723, BD) and intracellular staining with
antibodies were carried out by incubating first fixed and permeabilized cells in
Perm/Wash Buffer (cat# 554723, BD) with monoclonal rat antibody 2.4G2 and
subsequently with the desired antibodies in Perm/Wash Buffer at room temperature.
EdU was detected with Click-iT™ Plus EdU kits (cat# C10646, for AF594 and cat# C10636
for pacific blue, ThermoFisher Scientific). For double detection of EdU and BrdU, cells
were treated as for intracellular staining, but before adding the intracellular antibodies,
cells were treated with TURBO™ DNase (12 units/10^7 cells, cat# AM2239,
25 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
ThermoFisher Scientific) for 1 hour at 37oC, subsequently, EdU was detected with the
Click-iT™ reaction following the instructions from the manufacturer, cells were washed
with Perm/Wash Buffer (cat# 554723, BD) and incubated with anti-BrdU-AF647
antibody (MoBU-1, cat# B35133, ThermoFisher Scientific). DNA was stained in the last
step before flow cytometry analysis with 7AAD in EdU and BrdU double-labelling
experiments or with Vybrant™ DyeCycle™ Violet Stain in experiments where no DNA-
digestion was carried out (cat # V35003, ThermoFisher Scientific). In experiments where
cells were treated with etoposide to induce DNA damage, single cell suspensions from
bone marrow were incubated with 20μM etoposide (cat# E1383-100MG, Sigma) in RPMI
+2%FCS for 3 hours at 37oC. Flow cytometry data was acquired on a BD LSRFortessa with
5 lasers and was analysed using FlowJo software (versions 10.6.0 and 10.0.8r1).
mRNAseq libraries from FrB pro-B cells
FrB c-KIT+ pro-B cells (B220+, CD19+, IgD-, IgM-, CD2-, CD25-, CD43high, cKIT+, CD24+ and
CD249-) were sorted from bone marrow cells isolated from femurs and tibias. Bone
marrow cells from 4-6 mice from the same genotype and sex were pooled and depleted
of unwanted cells with anti Gr-1-bio (RB6-8C5), CD11b (M1/70), IgD-bio (11-26c.2a),
NK1.1-bio, CD3e (145-2C11) and Ter119 biotinylated antibodies and anti-biotin
microbeads (cat# 130-090-485, Miltenyi) before sorting. Sorting strategy of FrB pro-B
cells is shown in Supplementary Fig. 5. RNA from 15,000 to 200,000 FrB cells was
isolated with the RNeasy Micro Kit (cat# 74004, Qiagen). mRNAseq libraries from 5
biological replicates per genotype: (three genotypes: ctrl (Cd79a+/+Ptbp1fl/flPtbp2fl/fl),
P1sKO (Cd79acre/+Ptbp1fl/flPtbp2+/+) and P1P2dKO (Cd79acre/+Ptbp1fl/flPtbp2fl/fl); three
samples from females and two samples from males per genotype) were prepared by
generating cDNA from 2 ng RNA and 9 PCR cycles per replicate with the SMART-Seq® v4
26 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Ultra® Low Input RNA Kit for Sequencing (cat# 634891, Takara) and by enzymatic
fragmentation of 300 pg of cDNA followed by 12 PCR cycles using the Nextera XT DNA
Library Preparation Kit (cat# FC-131-1096, Illumina). Sequencing of the 15 mRNAseq
libraries multiplexed together was carried out with an Illumina HiSeq2500 on a 2x125
bp paired-end run.
PTBP1 iCLIP
PTBP1 iCLIP was carried out previously from mitogen-activated B cells (splenic B cells
stimulated with LPS for 48 hours)(Monzon-Casanova et al., 2018). This data was re-
analysed to map reads using a splicing-aware software. Reads from five PTBP1 iCLIP
libraries were mapped to the GRCm38.p5 mouse genome from Gencode with STAR (v
2.5.4b)(Dobin et al., 2013). Reads were de-duplicated using random barcodes included in
the library preparation and xlink-sites (Supplementary Table 1) and clusters of binding
(Supplementary Table 2) were identified with iCount
https://icount.readthedocs.io/en/latest/cite.html as previously described(Monzon-
Casanova et al., 2018). Detection of a binding site with iCLIP(König et al., 2010) is highly
dependent on the abundance of the RNA, therefore all replicates were pooled together to
identify xlink sites and clusters of binding. Xlink sites and clusters of PTBP1 binding were
assigned to transcripts and genomic features with the following hierarchy: CDS, 3’UTR,
5’UTR, intron, ncRNA using the Mus_musculus.GRCm38.93.gtf annotation from Ensembl
(Supplementary Tables 1, 2)
mRNA abundance analysis
mRNAseq libraries were trimmed with Trim Galore (v 1.15
https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) with default
27 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
parameters and mapped with Hisat2 (v 2.1.0) (Kim et al., 2015) with -p 7 -t --phred33-
quals --no-mixed --no-discordant parameters, the Mus_musculus.GRCm38 genome and
known splice sites from the Mus_musculus.GRCm38.90 annotation. Read counts mapped
over genes were counted with HTSeq (v0.10.0) (Anders et al., 2015) with f bam -r name
-s no -a 10 parameters and the Mus_musculus.GRCm38.93.gtf annotation from Ensembl.
Reads mapping to immunoglobulin genes (including V, D, J gene segments, light and
heavy immunoglobulin genes and T cell receptor genes) were excluded before DESeq2
analysis. Differences in mRNA abundance were computed with DESeq2 (v1.22.1) (Love
et al., 2014) by extracting differences between different genotypes in pair-wise
comparisons using “apeglm” method as a shrinkage estimator (Zhu et al., 2019).
Information on the sex of the mice from which the mRNAseq libraries were generated
was included in the design formula in addition to the genotype (design = ~ Sex +
Genotype). From the DESeq2 results we only considered genes with a mean expression
level of at least 1 FPKM (from the five biological replicates) in any of the three genotypes
analysed. FPKMs were calculated with cuffnorm from Cufflinks (v2.2.1) (Trapnell et al.,
2012) using the -library-norm-method geometric. We considered genes with differential
mRNA abundance as those with a log2-fold change >|0.5| and a p-adjusted value of <0.05
(Supplementary Table 3).
A gene with different mRNA abundance was bound by PTBP1 at the 3’UTR if at least one
cluster of PTBP1-binding from the PTBP1 iCLIP data (Supplementary Table 2) was
found to overlap with any 3’UTRs annotated in the Mus_musculus.GRCm38.93.gtf for that
gene after assignation to genomic features for the binding sites of the iCLIP as described
above.
28 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Genes with different mRNA abundance in P1P2dKO FrB pro-B cells compared to P1sKO
and control FrB cells (Fig. 3d, Supplementary Table 5) were identified after
hierarchical clustering of the Euclidian distances between Z-scores of each gene
calculated from the DESeq2 normalised read counts for the 15 mRNAseq libraries (5
biological replicates per genotype). Genes with different mRNA abundance in any of the
three pairwise comparisons carried out (Fig. 3a) were considered in the hierarchical
clustering.
Alternative splicing analysis
Trimmed reads with Trim Galore were further trimmed to 123 bp and reads which were
smaller than 123 bp were discarded with Trimmomatic (v0.35) (Bolger et al., 2014) in
order to obtain only pairs of reads 123 bp long. 123 bp-long reads were mapped to the
Mus_musculus.GRCm38 genome as described above, but only uniquely-mapped reads
were kept by using the -bS -F 4 -F 8 -F 256 -q 20 parameters in samtools when converting
hisat2 sam files to bam files. rMATS (Turbo v4.0.2) (Shen et al., 2014) was run with the -
t paired --readLength 123 parameters and the Mus_musculus.GRCm38.93.gtf annotation
for each individual pairwise comparison. Only results from rMATS with reads on exon-
exon junctions were considered further. Significantly differentially alternatively spliced
events (Supplementary Table 4) were defined as events that have an FDR<0.05, have
an absolute inclusion level difference >0.1, come from genes expressed with at least 1
FPKM (mean across five biological replicates in any of the genotypes analysed) and have
at least 80 reads from the sum of the five biological replicates mapping to either the
included or skipped alternatively spliced event in at least one of the two conditions
analysed. Only alternatively spliced events with the highest inclusion level difference
29 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
were kept from AS events with had the same genomic coordinates in the AS event
(Supplementary Table 4).
Proportions of differentially alternatively spliced events were defined as bound by PTBP1
(Supplementary Fig. 6e, Supplementary Table 4) with different rules depending on
the type of AS event. An SE was bound by PTBP1 if PTBP1 clusters (Supplementary
Table 2) were found on the SE, 500 nucleotides upstream or downstream of the AS SE,
on either of the constitutive flanking exons or in 500 nucleotides downstream or
upstream of the upstream and downstream constitutive exons, respectively. An A5SS was
bound if PTBP1 clusters were found on the longest exon containing the A5SS, on the
downstream intronic 500 nucleotides of the A5SS, on the downstream constitutive
flanking exon or the 500 intronic nucleotides upstream of the downstream constitute
flanking exon. An A3SS was bound by PTBP1 if PTBP1 clusters were found on the longest
exon containing the A3SS, the 500 intronic nucleotides upstream of the A3SS, the
upstream constitutive flanking exon or the 500 intronic nucleotides downstream of the
upstream constitutive flanking exon. A MXE was bound by PTBP1 if PTBP1 clusters were
found on either MXE, the upstream or downstream 500 intronic nucleotides of either
MXE, the upstream or downstream constitutive flanking exons or the downstream or
upstream 500 intronic nucleotides from the upstream or downstream constitutive
flanking exons, respectively. A RI was bound by PTBP1 if PTBP1 clusters were found on
the RI or on either constitutive flanking exon.
Events differentially alternatively spliced in P1P2dKO FrB pro-B cells compared to
control and P1sKO FrB pro-B cells (Fig. 3e) were identified by hierarchical clustering
using complete linkage clustering of the Euclidean distances between Z-scores of each AS
30 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
event calculated from the rMATS inclusion levels for the 15 mRNAseq libraries (5
biological replicates per genotype). AS events found in any of the three pairwise
comparisons (Fig. 3b) were used in the hierarchical clustering.
Gene ontology term enrichment analysis
Genes belonging to different clusters based on differences in mRNA abundance or AS
patterns between the P1P2dKO FrB pro B cells and the other genotypes (P1sKO and
Controls) (Fig. 3e, d and Supplementary Table 5) were used for gene ontology
enrichment analysis with GOrilla (Eden et al., 2009). Genes expressed with a mean of least
1 FPKM across the 5 biological replicates in any of the genotypes were used as
background list for expressed genes in FrB pro-B cells. Fig. 4a shows representative
enriched terms selected amongst closely related GO terms by manual inspection of the
ontology. Supplementary Table 5 is a full list of all enriched gene ontology enriched
terms. Representative selected terms are highlighted.
Comparison of transcriptomes from pro-B cells and mitogen activated B cells
Transcriptomes from control FrB pro-B cells and mitogen activated primary B cells (LPS
for 48 hours) (Diaz-Muñoz et al., 2015) were compared by calculating Spearman's rank
correlation of the Log mean TPM (Transcripts per million reads) for each gene. Mean
TPMs were calculated in FrB pro-B cells from five biological replicates and in mitogen-
activated B cells from four biological replicates. TPMs were calculated after counting
reads mapping to genes with HTSeq and the Mus_musculus.GRCm38.93.gtf annotation
from Ensembl.
mRNAseq from human PTBP1 and PTBP2 depleted HeLa
31 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Control and mRNAseq libraries where PTBP1 and PTBP2 were knocked down in HeLa
cells by Ling et al. (Ling et al., 2016) were trimmed with Trim Galore (v 0.6.2_dev) and
mapped with Hisat2 (v 2.1.0) (Kim et al., 2015) with --dta --sp 1000,1000 -p 7 -t --
phred33-quals --no-mixed --no-discordant parameters, the Homo_sapiens.GRCh38
genome annotation and a file with known splice sites generated from the
Homo_sapiens.GRCh38.87 annotation. Mapped reads were counted with HTSeq
(v0.10.0)(Anders et al., 2015) with -f bam -r name -s no -a 10 parameters and the
Homo_sapiens.GRCh38.93.gtf annotation from Ensembl. Read counts were normalised
with DESeq2 (Love et al., 2014) (v 1.20.0).
Statistical analysis
Statistical analysis of flow cytometry data was carried out with GraphPad Prism version
7.0e. Details of tests carried out are found in the legends. Statistical analysis of mRNAseq
data was carried out as described in the mRNA abundance analysis and Alternative
splicing analysis sections.
Data availability
mRNAseq libraries and iCLIP analysis generated in this study have been deposited in GEO
and can be accessed with the GSE136882 accession code at GEO. Mitogen activated
primary B cell mRNAseq libraries were previously reported and can be accessed with the
GSM1520115, GSM1520116, GSM1520117and GSM1520118 accession codes in GEO.
32 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Author contributions
E.M.C., M.T. and C.W.J.S. designed experiments. E.M.C. and K.T. performed experiments
and analysed data. E.MC., L.S.M. and K.Z. designed and carried out computational analysis.
E.M.C. and M.T. wrote the manuscript with input from the co-authors.
Acknowledgments
We thank Douglas L. Black for the Ptbp2fl/fl mice, Michael Reth for the Cd79acre mice,
Frederick W. Alt for the Rag2-/- mice and Michele Solimena for the Ptbp1fl/fl mice and the
anti-PTBP2 antibody; Kirsty Bates, Arthur Davis, Attila Bebes, Simon Andrews, the
Biological Support Unit, Flow Cytometry and Bioinformatics Facilities for technical
assistance; Tony Ly, Anne Corcoran and members of the Turner, Smith and Zarnack
laboratories for helpful discussions. This study was supported by funding from the
Biotechnology and Biological Sciences Research Council (BB/J00152X/1;
BB/P01898X/1; BBS/E/B/000C0407; and BBS/E/B/000C0427 and the Campus
Capability Core Grant to the Babraham Institute), a Wellcome Investigator award to M.T
and a Sort Term Scientific Mission Award to E.M.C. from the European Cooperation in
Science and Technology action CA17103, Delivery of Antisense RNA Therapeutics. The
authors declare no competing financial interests.
33 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
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39 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Figure Legends
Figure 1. Lack of PTBP1 and PTBP2 blocks B cell development.
a, Splenocytes pre-gated on live (eFluor780-) cells. Numbers in plots show proportions
of B cells from mice of the indicated genotypes. b, Numbers of B cells (B220+CD19+)
identified as shown in a per spleen from mice with the indicated genotypes. Data shown
is from one representative out of two independent experiments. c, Gating strategy based
on cell-surface markers for developing B cells from bone marrow cells pre-gated on dump
(Gr-1, CD11b, NK1.1, Siglec-F and F4/80)-negative live (eFluor780-) cells. Full gating
strategy is shown in Supplementary Fig. 1f. d, Numbers of developing B cells in the bone
marrow (2 femurs and 2 tibias per mouse) of mice with the indicated genotypes. b, d,
Bars depict means, each point represents data from an individual mouse and P-values
were calculated by one-way ANOVA with Tukey's multiple comparisons test. Summary
adjusted p value *<0.05, **<0.01, ***<0.001, ****<0.0001.
c, d, Data shown is from one representative out of three independent experiments with 4
to 5 mice per genotype (except for Rag2-/- mice from which one or two mice were
included) carried out with the same mouse genotypes shown except for the
CD79aCre/+Ptbp1+/+Ptbp2+/+ mice which were only included in the experiment shown here
(three CD79aCre/+Ptbp1+/+Ptbp2+/+ mice).
Figure 2. Cell cycle progression in Pro-B cells.
a, EdU and BrdU sequential labelling experimental set up to distinguish early, late and
post S-phase cells. b, Flow cytometry data of the different stages of S-phase in pro-B cells
(B220+CD19+IgD-surfaceIgM-intracellular-Igµ-CD43high) identified as shown in
Supplementary Fig. 3a. Numbers shown are proportions of cells. c, Percentages of pro-
40 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
B cells in different S-phase stages determined as shown in a and b. d, Number of pro-B
cells in bone marrow (2 femurs and 2 tibias per mouse) at different S-phase stages
determined as shown in b. e, Flow cytometry data of pro-B cells identified as shown in
Supplementary Fig. 3a and excluding BrdU+-only (cells in early S-phase). Numbers
shown are proportions of cells in the G2/M gate. f, Proportions and numbers (in 2 femurs
and 2 tibias per mouse) of pro-B cells in G2/M identified as shown in e. In c, d, f, bars
depict means, each point represents data from an individual mouse and P-values were
calculated by one-way ANOVA with Tukey's multiple comparisons test. Summary
adjusted p-value *<0.05, **<0.01, ***<0.001, ****<0.0001. b-f, data shown is from one of
two independent experiments.
Figure 3. PTBP1 and PTBP2 absence causes changes in mRNA abundance and AS.
a, Differences in mRNA abundance in pairwise comparisons from pro-B cell
transcriptomes. Shown are Log2Fold changes calculated with DESeq2 (Supplementary
Table 3). Red dots are values from genes with significant differences in mRNA abundance
(padj value <0.05) with a Log2Fold change > |0.5|. Grey dots are values from genes with
no significant differences (padj >0.05) or with a Log2Fold change < |0.5|. Numbers in
plots are the number of genes with increased or decreased mRNA abundance. b,
Differences in AS in pairwise comparisons from pro-B cells. Shown are inclusion level
differences >|0.1| with an FDR<0.05 for different types of alternatively spliced events:
skipped exons (SE), mutually exclusive exons (MXE), alternative 5’ and 3’ splice sites
(A5SS and A3SS, respectively), and retained introns (RI), (Supplementary table 4)
analysed with rMATS. Each dot shows the inclusion level difference for one event. c,
overlaps of genes that have changes in abundance and AS amongst the indicated pairwise
comparisons. d, Heatmap shows z-scores of normalised read counts from DESeq2 from
41 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
each biological replicate for genes that were found with differential mRNA abundance in
any of the three pair-wise comparisons shown in a. e, Heatmap shows z-scores of
inclusion levels from each biological replicate for those AS events that are alternatively
spliced in any of the three pair-wise comparisons shown in b. d, e, Hierarchical clustering
was done on Euclidean distances from z-scores and is shown with dendrograms.
Figure 4. Lack of global enrichment of proliferation-related terms amongst changes
in the transcriptome due to PTBP1 and PTBP2 absence.
a, Selected gene ontology (GO) terms (process and function) significantly (p-value <0.05)
enriched amongst genes that are differentially expressed at the abundance or the AS level
when comparing the transcriptome of P1P2dKO pro-B cells to P1sKO and control pro-B
cells as shown in Fig. 3d and e. Numbers show how many genes a GO term has.
Supplementary table 5 contains all significantly enriched GO process and function
terms. b, Log2-fold changes in mRNA abundance in the indicated pair-wise comparisons
for all tested genes (all genes), genes with increased abundance in S-phase (S) and G2/M-
phases (G2/M). Grey dots show genes with padj>0.05. Red dots amongst “all genes” show
genes with padj<0.05 and a >|0.5| log2-fold change. Red dots amongst S and G2M groups
show genes with a padj<0.05 regardless of their log2-fold change.
Figure 5. CDK inhibitors and CDK activity in P1P2dKO pro-B cells.
a, mRNA abundance of CDK inhibitors in pro-B cells from control, P1sKO and P1P2dKO
mice. Points show DESeq2 normalised read counts from individual pro-B cell mRNAseq
libraries. Bars depict means. DESeq2 calculated p-adjusted values are shown when <0.05
for the indicated pairwise comparisons. b, Intracellular flow cytometry with anti-p27
antibody or control isotype staining detected with an anti-rabbit AF647 conjugated
42 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
secondary antibody. c, Median fluorescence intensities (MFI) from staining shown in b.
d, Intracellular flow cytometry with the indicated antibodies. Numbers show proportions
of gated events. e, Proportions of cells identified as in d. b, d, Each histogram line shows
data from an individual mouse with the indicated genotype. FrB pro-B cells in G0/G1, S
or G2/M phases of the cell cycle were defined by EdU incorporation and DNA staining as
shown in Supplementary Fig. 3g. c, e, Points show data from individual mice. Bars depict
the mean. P-values were calculated by two-way ANOVA with Tukey's multiple
comparisons test. Summary adjusted p value *<0.05, **<0.01, ***<0.001, ****<0.0001.
b – e, Data is from one experiment with four to five mice per genotype. The differences
observed for pT592-SAMHD1 and pS807/S811-RB between control and P1P2dKO cells
were confirmed in an independent experiment where two control and two P1P2dKO mice
were used.
Figure 6. Cell cycle regulators in the absence of PTBP1 and PTBP2.
a, mRNA abundance of cell cycle regulators in pro-B cells from control, P1sKO and
P1P2dKO mice. Genes whose names are in yellow and bold are predicted to have reduced
mRNA abundance due to changes in AS upon Ptbp1 and Ptbp2 deletion. Individual data
points show DESeq2 normalised read counts from individual pro-B cell mRNAseq
libraries. Bars depict means. DESeq2 calculated adjusted p-values are shown when <0.05
for the indicated pairwise comparisons. b, PTBP1 iCLIP and mRNAseq data visualisation.
For PTBP1 iCLIP, x-link sites are shown for all events. Clusters of PTBP1 binding are
shown when found. mRNAseq data from pro-B cells of one replicate per genotype is
shown using sashimi plot visualisation from IGV. Numbers on the left show the maximum
number of reads in the coverage plots. Arcs depict exon-exon junctions detected in
mRNAseq reads. Numbers in arcs show the number of reads for the depicted exon-exon
43 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
junction. Parts of transcript isoforms predicted to be degraded by NMD are shown in
yellow. Parts of transcript isoforms coding for proteins are shown in blue. Exon numbers
of transcript isoforms coding for proteins are shown with E and a number. c, mRNAseq
visualisation as in b from HeLa control cells or cells where PTBP1 and PTBP2 were
knocked down (Ling et al., 2016). d, Human RBL1 normalised DESeq2 read counts from
the two mRNAseq libraries (one control and 1 double knock down) shown in c. e,
Representation of cell cycle mRNA regulon controlled by PTBP1 in pro-B cells and
consequences of Ptbp1 and Ptbp2 deletion in pro-B cells. Depicted interactions of PTBP1
with individual factors are likely to be direct.
SUPPLEMENTARY FIGURES:
Supplementary Figure 1. PTBPs expression in developing B cells.
a, Representation of B cell development in the bone marrow using the Philadelphia
nomenclature (Hardy and Hayakawa, 2003) including Hardy’s fractions (Fr) based on
cell-surface markers (Hardy et al., 1991). b, Identification strategy of bone marrow cells
using cell-surface and intracellular markers. c, PTBP1, PTBP2 and PTBP3 expression
analysed by flow cytometry. Identification of different B cell developmental stages was
carried out as shown in b. d, Geometric fluorescence mean intensity (gMFI) of staining
for PTBP1, PTBP1, PTBP3 and control isotypes as shown in c. Bars depict means. Each
data point shows data from an individual control mouse (CD79a+/+Ptbp1fl/flPtbp2fl/fl). Data
shown is from one experiment with 5 mice. e, Numbers and proportions of B cells
(eFluor780-B220+CD19+) in mesenteric lymph nodes. f, Complete gating strategy of cells
from bone marrow using cell surface markers to identify developing B cells and Hardy’s
fractions B, C and C’ as shown in Fig. 1c. Dump contains Gr-1, CD11b, NK1.1, Siglec-F and
44 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
F4/80. Data shown is from a Ctrl (CD79a+/+Ptbp1fl/flPtbp2fl/fl) mouse. b, f, numbers
indicate proportions of gated populations.
Supplementary Figure 2. B cell development characterisation in the absence of
PTBP1 and PTBP2
a, Cell surface and intracellular staining strategy to define B cell developmental stages in
bone marrow cells from mice of the indicated genotypes. Numbers shown are
percentages of gated events. b, PTBP1, PTBP2 and PTBP3 detection and negative isotype
control staining in different B cell developmental stages identified as shown in a. Data
shown is of a representative mouse out of five for each genotype indicated. Data shown
is from one experiment. c, c-KIT and CD2 expression at different B cell developmental
stages in mice of the indicated genotypes. Identification of different B cell developmental
stages was done as shown in Supplementary Fig. 1f. a, b, c, data shown is representative
from one mouse out of five mice per genotype, except for Rag2-/- mice for which only two
were included. d, c-KIT median fluorescence intensity (MFI) in pro-B cells (FrB and FrC)
identified as shown in c. c, d, Data shown is from one out of three independent
experiments. e, Numbers of developing B cells in bone marrow from two femurs and two
tibias identified as shown in a with a combination of cell-surface and intracellular
staining. Data shown is from one experiment. d, e Bars show means, each point
represents data from an individual mouse, P-values were calculated by one-way ANOVA
with Tukey's multiple comparisons test. Summary adjusted p value *<0.05, **<0.01,
***<0.001, ****<0.0001.
Supplementary Figure 3. Cell cycle analysis in developing B cells.
45 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
a, Gating strategy identifying pre-pro-, pro- and early-pre-B cells in EdU and BrdU
sequential labelling experiments for bone marrow live cells from the indicated genotypes.
b, Early-, late- and post-S-phase gating amongst pre-pro-, pro- and early-pre-B cells
identified as shown in a. c, Proportions of early, late and post S-phase cells amongst pre-
pro-, pro- and early-pre-B cells identified as shown in a and b. d, Numbers of early-, late-
and post-S-phase pre-pro-, pro- and early-pre-B cells identified as shown in a and b in
two tibias and two femurs per mouse. e, Gating strategy to identify cells in G2/M phases
amongst pre-pro-, pro- and early-pre-B cells identified as shown in a. Events shown are
pre-gated excluding cells in early S-phase (BrdU+-only). f, Proportions and numbers (in
two tibias and two femurs per mouse) of G2/M pre-pro-, pro- and early-pre-B cells
identified as shown in a and e. g, Identification strategy of proliferating FrB pro-B cells
amongst bone marrow cells from mice with the indicated genotypes. Mice were injected
with EdU i.p. for one hour before analysis to track cells in G0/G1, S and G2/M phases of
the cell cycle. h, Proportions of FrB developing B cells in G0/G1, S and G2/M phases
defined as shown in g. i, Phospho-histone 3 serine 10 (pH3 S10) staining amongst FrB
pro-B cells identified as in g. j, Percentages of pH3(S10)-positive cells amongst cells with
duplicated DNA amounts (4n) in pro-B cells (FrB) assessed by flow cytometry as shown
in i. a, b, e, g, i, Numbers shown indicate proportions. c, d, f, h, j Bars show means, each
point shows data from an individual mouse and P-values were calculated by one-way
ANOVA with Tukey's multiple comparisons test. Summary adjusted p value *<0.05,
**<0.01, ***<0.001, ****<0.0001. c, d, f, Data shown is from one out of two independent
experiments. h, j, Data shown is from one out of three independent similar experiments.
Supplementary Figure 4. DNA-damage assessment in PTBP1 and PTBP2 deficient
FrB pro-B cells.
46 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
a, FCS-A measurements of FrB pro-B cells in different phases of the cell cycle identified
as in Supplementary Fig. 3g. b, Intracellular staining with anti-pH2AX or an isotype
control. c, MFIs (median fluorescence intensity) from the staining shown in b and fold
changes in MFIs from intracellular staining with pH2AX and isotype control antibodies
between FrB pro-B cells from P1sKO (CD79aCre/+Ptbp1fl/flPtbp2+/+) and control (Ctrl,
CD79a+/+Ptbp1fl/flPtbp2fl/fl or +/+) mice or from P1P2dKO (CD79aCre/+Ptbp1fl/flPtbp2fl/fl) and
control mice in different cell cycle phases from the data shown in b. d, Intracellular
staining with anti-pH2AX FrB pro-B cells in different cell cycle phases. Bone marrow cells
were either stained on their cell surface to identify FrB pro-B cells and fixed before
intracellular staining, EdU and DNA detection (ex vivo) or were incubated with 20 µM
Etoposide in RPMI at 37oC for 3 hours before cell surface staining to identify FrB pro-B
cells (+Etoposide). f, MFIs from staining shown in d and fold changes in MFIs calculated
as described in c. f, Intracellular staining with anti-p53 antibody or with an isotype
control in FrB pro-B cells. Cells were analysed after isolation from the bone marrow (ex
vivo) or after treatment with etoposide as described in d. g, MFIs from the staining shown
in f and fold change in MFI for the different staining as described in c. In a, b, d, and f FrB
pro-B cells were identified in different phases of the cell cycle by EdU incorporation and
DNA staining as shown in Supplementary Fig. 3g. In a, b, d and f, each histogram line
shows data from an individual mouse. In a, c, e and g Each point shows data from an
individual mouse. Bars show means. P-values were calculated by two-way ANOVA with
Tukey's multiple comparisons test. Summary adjusted p value *<0.05, **<0.01, ***<0.001,
****<0.0001. a, data shown is representative from one out of three independent
experiments. b, c, Data is representative from one out of two independent experiments.
d, e, f, g data shown is from one experiment where the treatment with etoposide was
included. Differences in p53 staining levels between FrB pro-B cells from P1P2dKO and
47 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
control mice were confirmed in an independent experiment where two P1P2dKO mice
and two control mice were analysed.
Supplementary Figure 5. Cell sorting strategy of pro-B cells.
a, Cell sorting strategy of FrB pro-B (B220+CD19+IgM-IgD-CD2-CD43highCD25-
cKIT+CD24+CD249+) cells used to isolate RNA and carry out mRNAseq libraries. Dump
contains IgM, CD2 and streptavidin. Prior sorting, bone marrow cells were depleted from
Gr-1, CD11b, IgD, NK1.1, CD3e and Ter119-positive cells.
Supplementary Figure 6. Transcriptome analysis of pro-B cells.
a, Transcriptome correlation in mitogen-activated primary B cells and FrB pro-B cells.
Dots show mean values of TPMs (transcripts per million) from four or five biological
replicates in mitogen-activated B cells and pro-B cells, respectively. Correlation was
calculated with Spearman's rank correlation rho on genes with >= 1 TPM in pro-B cells
and >0 TPM in mitogen-activated B cells (12545 genes). 681 genes had 0 TPMs in
mitogen-activated B cells and >=1 TPM in pro-B cells. b, Proportions of genes with
differences in mRNA abundance for the indicated pairwise comparisons that are bound
by clusters of PTBP1 (iCLIP data) on their 3’UTR (Supplementary Tables 2 and 3). c,
Ptbp2 mRNAseq visualisation with Sashimi coverage plots done with IGV showing one
replicate per genotype. Arches depict reads mapping to two different exons. Numbers on
arches show the number of reads that map to that particular exon-exon junction.
Numbers in black on the left show the maximum number of reads in the coverage plots.
d, Different types of alternatively spliced events analysed with rMATS. e, Proportions of
AS changes between the indicated comparisons that are bound by at least one PTBP1
cluster in the vicinity of the alternatively spliced event (see methods for definition of
48 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
vicinity, Supplementary Tables 2 and 4). f, mRNA abundance of B cell development
regulators in pro-B cells. DESeq2 normalised read counts of the indicated genes. DESeq2
calculated padj values are shown when <0.05. Bars show means. Each dot shows data
from an individual mRNAseq biological replicate.
Supplementary Figure 7. PTBP1 binding to target transcripts
a, PTBP1 binding (iCLIP data) to 3’UTRs. b, Intracellular c-MYC or control isotype staining
of FrB pro-B cells in different stages of the cell cycle identified as shown in
Supplementary Fig. 3g. Each line shows data from one individual mouse. c, Median
fluorescence intensities (MFI) from the staining shown in b. Each point shows data from
an individual mouse. Bars show means. P-values were calculated by two-way ANOVA
with Tukey's multiple comparisons test. Summary adjusted p value *<0.05, **<0.01,
***<0.001, ****<0.0001. Data shown is from one representative out of two independent
experiments.
SUPPLEMENTARY TABLES:
Supplementary Table 1. PTBP1 binding sites (xlinks).
Supplementary Table 2. PTBP1 binding sites (clusters).
Supplementary Table 3. mRNA abundance analysis. DESeq2 results shown in Fig. 3a.
Separate tabs show genes with significant differential (padj<0.05) mRNA abundance with
a log2 fold change > |0.5| for the different pairwise comparisons carried out and also all
the results obtained with DESeq2. Additional tabs shown genes whose transcripts were
bound by PTBP1 clusters at their 3’UTR.
49 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
Supplementary Table 4. AS analysis. Different tabs show inclusion level differences
(IncLevelDifference) shown in Fig. 3b for the three pairwise comparisons carried out. The
first three tabs show significant (FDR <0.05) alternatively spliced events with an absolute
inclusion level difference >0.1. “allresults” tabs show all the results from rMATS. “PTBP1
bound” tabs show those significantly differentially spliced events that were bound in
their vicinity by PTBP1 clusters.
Supplementary table 5. Gene ontology enrichment analysis. Results from gene ontology
enrichment analysis carried out with the groups of genes identified in Fig. 3d, e.
Supplementary Table 6. DESeq2 results for genes shown to have high mRNA expression
levels in S or G2M phases (Giotti et al., 2018) in the three pair-wise comparisons shown
in Fig. 4b.
Supplementary Table 7. Antibodies and reagents used in flow cytometry experiments.
50 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
a Ctrl P1sKO P1P2dKO b CD79a+/+ CD79aCre/+ CD79aCre/+ Ptbp1fl/flPtbp2fl/fl Ptbp1fl/flPtbp2+/+ Ptbp1fl/flPtbp2fl/fl 8 **** 5 +/+ fl/fl fl/fl 10 * **** Ctrl (CD79a Ptbp1 Ptbp2 ) Cre/+ fl/fl +/+ 4 6 P1sKO (CD79a Ptbp1 Ptbp2 ) 10 )/spleen 7 (CD79aCre/+ Ptbp1fl/flPtbp2fl/fl) 48.1 55.4 0.10 P1P2dKO 3 10 4
CD19-BUV737 0 2 3 4 5 0 10 10 10
B220-BUV395 # B cells (x10 0
c Mat. recirc. 10.4 Immature 22.3 14.6 72.8 11.7 26.9 pro 33.5 early-pre pre-pro (FrC) 81.7 (FrC’) Ctrl 41.6 pro CD79a+/+ (FrB) Ptbp1fl/flPtbp2fl/fl 89.5 Late pre 41.8
16.8 13.7 20.4 79.4 14.2 20.1 61.1
76.9 P1sKO 40.7 CD79aCre/+ 22.7 Ptbp1fl/flPtbp2+/+ 83.0
0.12 39.0 94.1 45.9 0.027 53.5 0.77
2.77 P1P2dKO Cre/+ 5.03 CD79a fl/fl fl/fl 56.5 Ptbp1 Ptbp2 99.8
250K 5 4 5 10 0.12 10 78.7 10 62.4 4 13.7 86.2 1.65 0.11 10 200K 4 4 10 10 3 150K 10 3 17.0 -/- 10 3 Rag2 3 10 10 20.9 100K
0 0 50K 25.4 99.8 0 0 IgD- PerCPCy5.5 CD43-bio + SA-BV510 IgM-BV785 FCS-A 0 3 4 3 4 3 4 3 4 5 CD249(BP1)-PE 3 4 5 0 10 10 0 10 10 0 10 10 0 10 10 10 0 10 10 10 IgM-BV785 B220-BUV395 CD25-BV650 CD19-BUV737 CD24(HSA)-FITC
Pre pro (FrA) Pro (FrB) Pro (FrC) Early pre (FrC’) **** d **** * **** **** **** *** ** * 10 15 **** 35 **** 25 **** * **** 20 **** **** 25 5 5 5 5 10 6 15 5 x1 0 x1 0 x1 0 x1 0 4 10
# cells 5 2 5 0 0 0 0
Late Pre (FrD) Immature (FrE) Mature recirc. (FrF) *** **** **** Cre/+ +/+ +/+ *** **** **** mb1 (CD79a Ptbp1 Ptbp2 ) **** **** **** 20 6 * **** 12 *** +/+ fl/fl fl/fl **** **** Ctrl (CD79a Ptbp1 Ptbp2 ) **** **** **** * **** 15 **** P1sKO (CD79aCre/+Ptbp1fl/flPtbp2+/+) 6 6 6 4 8 10 P1P2dKO (CD79aCre/+ Ptbp1fl/flPtbp2fl/fl) x1 0 x1 0 x1 0
# cells 2 4 -/- 5 Rag2
0 0 0
Figure 1 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Ctrl CD79a+/+ P1sKO CD79aCre/+ P1P2dKO CD79aCre/+ a b Ptbp1fl/flPtbp2fl/fl Ptbp1fl/flPtbp2+/+ Ptbp1fl/flPtbp2fl/fl 5 EdU BrdU 10 -1h 40’ -40’ Early Late 2.3 13.7 2.7 13.5 9.7 36.3 4 S S 10
3 10 Post 2 S 10
BrdU 0 82.2 1.7 82.0 1.8 50.2 3.3 BrdU-AF647 2 3 4 5 EdU 0 10 10 10 10 EdU-PB c **** d 12 10 ) ) 60 4 10 * ) **** +/+ 4 * Ctrl (CD79a *** 3 12 3 15 +/+ fl/fl fl/fl ) **** 8 Ptbp1 Ptbp2 ) 5 8 *** Ctrl (CD79a fl/fl fl/fl 8 **** Cre/+ Ptbp1 Ptbp2 ) 40 ** P1sKO (CD79a 2 6 6 8 10 Cre/+ * Ptbp1fl/flPtbp2+/+) P1sKO (CD79a 4 Ptbp1fl/flPtbp2+/+) P1P2dKO (CD79aCre/+ 4 4 20 1 4 5 Cre/+ % Late S % Post S % Early S fl/fl fl/fl P1P2dKO (CD79a 2 Ptbp1 Ptbp2 ) # Pro B (x1 0 2 Ptbp1fl/flPtbp2fl/fl) # Early S pro B (x1 0 # post S pro B (x1 0 0 0 0 0 0 # Late S pro B (x1 0 0 0
Ctrl CD79a+/+ P1sKO CD79aCre/+ P1P2dKO CD79aCre/+ e fl/fl fl/fl Ptbp1fl/flPtbp2+/+ Ptbp1fl/fl fl/fl f Ptbp1 Ptbp2 Ptbp2 * **** * 20 ) 3 5 **** 4 10 Ctrl (CD79a+/+ 15 fl/fl fl/fl 4 Ptbp1 Ptbp2 ) 10 2 P1sKO (CD79aCre/+ 3 10 fl/fl +/+ 10 Ptbp1 Ptbp2 ) Cre/+ 0.18 0.21 11.4 % G2/M 1 P1P2dKO (CD79a 2 5 10 G2/M G2/M G2/M Ptbp1fl/flPtbp2fl/fl) # G2/M pro B (x1 0 EdU-PB 0 0 0 0 50K 100K 150K 200K250K DNA (7AAD) Figure 2 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. a P1sKO vs Ctrl P1P2dKO vs Ctrl P1P2dKO vs P1sKO
4 107 Ptbp2 4 468 4 484 Ciita H2-Aa 3 3 Ptbp2 3 H2-Eb1 Increased Increased Cd74 Increased in P1sKO Cd74 in P1P2dKO H2-Aa in P1P2dKO 2 Capza1 2 2 vs Ctrl vs Ctrl vs P1sKO 1 1 1 0 0 0
−1 Dpp4 Decreased −1 Cd79a Decreased −1 Decreased −2 Ptbp1 in P1sKO −2 Ptbp1 in P1P2dKO −2 Ect2 in P1P2dKO Ect2 −3 vs Ctrl −3 vs Ctrl −3 Iqgap1 vs P1sKO Mpo Log2 fold change Mpo Elane −4 107 −4 758 Elane −4 718 1 100 10000 1 100 10000 1 100 10000 Normalised read counts (base mean) b P1sKO - Ctrl P1P2dKO - Ctrl P1P2dKO - P1sKO 348 44 32 31 43 1165 198 62 103 71 568 92 30 54 66 1.0 1.0 1.0 More More More included included in included in 0.5 in P1sKO 0.5 P1P2dKO 0.5 P1P2dKO vs Ctrl vs Ctrl vs P1sKO
0.0 0.0 0.0 More More More skipped skipped in skipped in −0.5 in P1sKO −0.5 P1P2dKO −0.5 P1P2dKO vs Ctrl vs Ctrl vs P1sKO −1.0 274 43 13 20 17 −1.0 632 90 35 61 32 −1.0 533 108 27 42 39
Inclusion level difference SE MXE A5SS A3SS RI SE MXE A5SS A3SS RI SE MXE A5SS A3SS RI Alternatively spliced event type c P1sKO vs Ctrl P1P2dKO vs Ctrl P1P2dKO vs P1sKO
Different mRNA abundance 181 1078 1117 33 Different 626 148 85 alternative splicing 910 520
d ≠ mRNA abundance e ≠ alternative splicing
−3 0 3 −20 2 Z−score # genes Z−scores (normalised read (inclusion levels) # events counts) Ctrl P1sKO P1P2dKO (cluster) Ctrl P1sKO P1P2dKO (cluster) 182(i)
566 (a) 801 1021 (ii)
455 from 971 (b) 166 (iii) genes
596 611 (c) (iv)
(d) 354 54 (v) 98 (e)
Figure 3 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. a Increased mRNA abundance in P1P2dKO vs Ctrl & P1sKO # genes ag processing and presentation of peptide ag via MHC class II 15 ribosome biogenesis 90 ribonucleoside biosynthetic process 22 rRNA processing 165 neural crest cell migration 14
0 25 50 75 100 % of genes
Decreased mRNA aundance in P1P2dKO vs Ctrl & P1sKO # genes cyclin-dependent protein serine/threonine kinase inhibitor activity 9 lipid catabolic process 123 myeloid cell activation involved in immune response 21 cytokine secretion 24 neutrophil migration 32 response to catecholamine 14 response to lipopolysaccharide 121 positive regulation of protein secretion 127 positive regulation of DNA-binding transcription factor activity 142 positive regulation of glycolytic process 9 positive regulation of MAPK cascade 223 positive regulation of innate immune response 103 regulation of neuron differentiation 362 positive regulation of interleukin-6 production 40
0 25 50 75 100 % of genes
Alternatively spliced in P1P2dKO vs Crl &P1sKO # genes
cytoskeletal protein binding 495
histone H4-K5 acetylation 13
peptidyl-lysine acetylation 89 regulation of neuron differentiation 361 regulation of endocytosis 166 regulation of cytokine-mediated signaling pathway 67
0 25 50 75 100 % of genes b P1sKO vs Ctrl P1P2dKO vs Ctrl P1P2dKO vs P1sKO 4 4 4 3 3 3 Increased Increased Increased 2 in P1sKO 2 in P1P2dKO 2 in P1P2dKO vs Ctrl vs Ctrl vs P1sKO 1 1 1 0 0 0 −1 −1 −1 Decreased Tyms Decreased Decreased −2 in P1sKO −2 Kif2c in P1P2dKO −2 Cdc25b in P1P2dKO vs Ctrl Cdc25b vs Ctrl vs P1sKO −3 −3 Ect2 −3 Ect2
Log2 Fold Change −4 −4 −4 All genes S G2/M All genes S G2/M All genes S G2/M
Figure 4 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.
a Cdkn1a (p21) Cdkn1b (p27) Cdkn1c (p57) Cdkn2c (p18) Cdkn2d (p19) +/+ 0.025 <0.0001 Ctrl (CD79a <0.0001 0.0017 <0.0001 0.017 fl/fl fl/fl 1.0 6 <0.0001 10 <0.0001 Ptbp1 Ptbp2 ) 6 6 0.002 <0.0001 P1sKO (CD79aCre/+ 8 Ptbp1fl/flPtbp2+/+) 2 3 3 3 4 4 2 4 6 P1P2dKO (CD79aCre/+ x10 x10 x10 x10
x1 0 0.5 fl/fl fl/fl 4 Ptbp1 Ptbp2 ) 2 2 2 2
Norm. read counts 0 0 0.0 0 0
Ctrl (CD79a+/+Ptbp1fl/flPtbp2fl/fl or +/+) b G0/G1 S G2/M c P1sKO (CD79aCre/+Ptbp1fl/flPtbp2+/+) P1P2dKO (CD79aCre/+Ptbp1fl/flPtbp2fl/fl)
Ctrl 20 *** ) P1sKO 2 15 *** P1P2dKO 10 3 4 5 3 4 5 3 4 5
0 10 10 10 0 10 10 10 0 10 10 10 MFI (x1 0 5 Rabbit IgG + anti-Rab.-AF647 0
Rab Ab + 2ary-AF647 G0/G1 S G2/M ****
) 6
4 **** Ctrl 4 **** P1sKO **** 2
P1P2dKO p27 MFI (x10 3 4 5 3 4 5 3 4 5 0 10 10 10 0 10 10 10 0 10 10 10 0 p27 + anti-Rab.-AF647 G0/G1 S G2/M
G0/G1 S G2/M Ctrl (CD79a+/+Ptbp1fl/flPtbp2fl/fl or +/+) e Cre/+ fl/fl +/+ d 100 33.1 98.7 79.5 P1sKO (CD79a Ptbp1 Ptbp2 ) 80 Cre/+ fl/fl fl/fl 60 P1P2dKO (CD79a Ptbp1 Ptbp2 )
Modal 40 20 0 Ctrl **** 100 **** 100 95.1 **** ** **** 80 16.4 66.1 60 1 RB +
Modal 40 20 50 0 P1sKO *** 100 99.0 80 86.9 35.7 60
Modal 40 % pS807/7 1 0 20 P1P2dKO G0/G1 S G2/M 0 3 4 5 3 4 5 3 4 5 0 10 10 10 0 10 10 10 0 10 10 10 100 pS807/811 RB-AF647 **** **** **** **** 100 50 80 9.65 96.4 49.4 60
Modal 40 * 20 0 Ctrl 0 100 % pT592 SAMHD1 + G0/G1 S G2/M 80 3.99 95.8 55.5 60
Modal 40 20 0 P1sKO 100 80 55.8 97.6 8.72 60
Modal 40 20 P1P2dKO 0 3 4 5 3 4 5 3 4 5 0 10 10 10 0 10 10 10 0 10 10 10 pT592 SAMHD1 + anti-Rab.-AF647
Figure 5 bioRxiv preprint doi: https://doi.org/10.1101/769141; this version posted September 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made a Foxo1 Myc Ccnd2available underBtg2 aCC-BY-NCRbl1 4.0 (p107) InternationalCdc25b license . Ect2 Kif2c Kif22 <0.0001 <0.0001 <0.0001 10 <0.0001 16 6 <0.0001 15 0.0002 <0.0001 2 12 <0.0001 3 <0.0001 <0.0001 15 <0.0001 0.001 <0.0001 8 <0.0001 2 <0.0001 <0.0001 <0.0001 12 9 <0.0001
3 3 3 4
3 4 4 3 6 3 4 10 10 2
x10
x10 x10
x10 x10 x1 0 x1 0 x1 0 x10 8 1 6 4 1 2 5 5 1 2 4 3 Norm. read counts 0 0 0 0 0 0 0 0 0 Ctrl (CD79a+/+Ptbp1fl/flPtbp2fl/fl) P1sKO (CD79aCre/+Ptbp1fl/flPtbp2+/+) P1P2dKO (CD79aCre/+Ptbp1fl/flPtbp2fl/fl)
Rbl1 (p107) b 3 PTBP1 clusters Kif2c iCLIP 0 2 PTBP1 2 PTBP1 x-link sites x-link sites 0 0 [0 - 660] 619 593 [0 - 1018] 956 698 Control 6 Control
1027 [0 - 654] 565 527 mRNA [0 - 1115] 705 seq P1sKO 9 P1sKO 13 5
563 300 [0 - 605] 375 [0 - 362] 264 26 19 34 P1P2dKO 6 P1P2dKO 7 8 PC PC NMD NMD E7 E8 A5’SS (NMD-triggering exon) E9 E2 NMD-exon E3 E4
Ect2 5 PTBP1 clusters Kif22 0 4 PTBP1 2 PTBP1 x-link sites 0 x-link sites 0 [0 - 870] 712 [0 - 3057] 1904 14 Control Control [0 - 955] 862 [0 - 2711] 9 P1sKO 1433 P1sKO 19 31 73 9 [0 - 177] 42 [0 - 1396] 40 732 24 P1P2dKO 61 104 P1P2dKO 13 PC PC NMD NMD E2 NMD-exon E19 NMD-exon E20 E3
Human RBL1 (p107) c Human RBL1 (p107) [0 - 294] 209 238 d
11 Control ) 4
3 Control HeLa 3 P1P2 KD HeLa [0 - 119] 105 67 36 PTBP1 and 2 PTBP2 KD 1
PC Counts (x1 0 NMD Normalised Read 0 E7 E8 A5’SS E9 (NMD-triggering exon)
e PTBP1 & PTBP2 deficient pro B cells pro B cells - little proliferation enhanced entry into S & block at G2
PTBP1 PTBP1 PTBP1 PTBP1 c-MYC c-MYC x p107 x pT592 p107 FOXO1 P P SMADH1 CYCLIN D2 RB P FOXO1 CYCLIN D2 p27 CDK 4,6 Ccna2, Ccne1... RB Cdk1, Cdk2 CDK 4,6 Ccna2, Ccne1... E2F p27 Cdk1, Cdk2 E2F G0 G1 G1 CYCLIN A,E G0 KIF2c PTBP1 CDK 2 CYCLIN A,E KIF2c KIF22 M S PTBP1 CDK 2 TYMS KIF22 M S ECT2 ECT2 x TYMS G2 PTBP1 G2 PTBP1 pT592 P CYCLIN A,B CYCLIN A,B SMADH1 pT592 CDK 1 CDC25B P SMADH1 CDK 1 CDC25B x
p27 p27 Figure 6